Quality Analytics Engineer III
Waukesha, WI - USA
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in Data Science, Computer Science, Statistics, Analytics, Engineering, Industrial Engineering, or a related field is required.
- 5+ years in analytics, with significant experience in data strategy, business intelligence, advanced analytics.
- Deep experience with data modeling, cloud platforms (e.g., Databricks), and large-scale data systems.
- Demonstrated experience supporting quality, warranty, manufacturing, reliability, operational performance, or continuous improvement initiatives through data-driven insights.
- Experience developing dashboards, scorecards, and analytical solutions that support quality and operational decision-making.
- Experience with power generation development and technology.
Preferred experience
- Master's degree in a quantitative field is preferred.
- Experience with trend analysis, root cause analysis, KPI development, statistical analysis, and process improvement methodologies preferred.
Qualification wording
Bachelor's degree in Data Science, Computer Science, Statistics, Analytics, Engineering, Industrial Engineering, or a related field is required. Master's degree in a quantitative field is preferred.
5+ years in analytics, with significant experience in data strategy, business intelligence, advanced analytics.
Deep experience with data modeling, cloud platforms (e.g., Databricks), and large-scale data systems.
Demonstrated experience supporting quality, warranty, manufacturing, reliability, operational performance, or continuous improvement initiatives through data-driven insights.
Experience developing dashboards, scorecards, and analytical solutions that support quality and operational decision-making.
Experience with power generation development and technology.
Experience with trend analysis, root cause analysis, KPI development, statistical analysis, and process improvement methodologies preferred.
Tools in this posting
- Python
- R
- SQL
- Databricks
Source — Tool mentions in context
Technical Skills: - Expert-level SQL and Python (or R). - Deep experience with data modeling, cloud platforms (e.g., Databricks), and large-scale data systems.
- Expert-level SQL and Python (or R). - Deep experience with data modeling, cloud platforms (e.g., Databricks), and large-scale data systems. - Advanced proficiency in BI tools and statistical modeling packages.
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier listing.
- Status in our records
- Live
- First seen by us
- Oct 21, 2026 · today
- Recorded sightings
- 1
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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Job description
For more than 65 years, we've turned big ideas into solutions that help protect homes, strengthen businesses and build a more resilient, efficient, sustainable energy future.
Ready to Power a Smarter World with us?
The Analytics Engineer III leads complex analytical initiatives, from defining data strategy to deploying predictive and analytical solutions that drive business effectiveness through improvements in product quality, operational performance, and customer experience. This role partners across quality, engineering, operations, and executive leadership to influence strategic decisions, guide analytical investigations, and scale self-service analytics. It combines deep technical skills with strong business acumen and mentorship.
Major Responsibilities:
Strategic Collaboration & Influence:
- Act as a thought partner to leaders, identifying opportunities for analytics to improve product quality, reliability, operational effectiveness, and customer satisfaction.
- Lead requirements gathering for complex, cross-functional initiatives.
Architecture & Reporting Strategy:
- Architect scalable reporting frameworks and advanced data models across the quality, warranty, manufacturing, and operational analytics ecosystem.
- Oversee the delivery of high-impact dashboards and insights for executive-level reporting.
Advanced Modeling & Analysis:
- Develop sophisticated analytical and predictive models to identify quality trends, warranty drivers, failure patterns, process variation, and emerging product risks.
- Design and validate complex analytical studies to evaluate corrective actions, process improvements, quality initiatives, and operational performance outcomes.
- Apply statistical techniques to identify trends, anomalies, and opportunities for continuous improvement.
Data Infrastructure Leadership:
- Partner with data engineering to design robust ETL processes and scalable infrastructure.
- Drive improvements in data architecture for quality, warranty, manufacturing, supplier, and operational analytics, including real-time data integrations.
Process Optimization & Automation:
- Lead initiatives to automate data processes and enhance operational efficiency.
- Standardize quality and operational KPIs and promote data governance best practices across teams.
- Drive adoption of consistent metrics, reporting methodologies, and data standards to support quality performance management.
Mentorship & Enablement:
- Provide technical mentorship to junior team members.
- Champion a culture of self-service analytics by developing training and tools for business users.
- Support quality and operational teams in leveraging analytics to drive data-informed decision-making.
Minimum Job Requirements:
Education:
- Bachelor's degree in Data Science, Computer Science, Statistics, Analytics, Engineering, Industrial Engineering, or a related field is required. Master's degree in a quantitative field is preferred.
Experience:
- 5+ years in analytics, with significant experience in data strategy, business intelligence, advanced analytics.
- Demonstrated experience supporting quality, warranty, manufacturing, reliability, operational performance, or continuous improvement initiatives through data-driven insights.
- Experience with trend analysis, root cause analysis, KPI development, statistical analysis, and process improvement methodologies preferred.
Technical Skills:
- Expert-level SQL and Python (or R).
- Deep experience with data modeling, cloud platforms (e.g., Databricks), and large-scale data systems.
- Advanced proficiency in BI tools and statistical modeling packages.
- Experience developing dashboards, scorecards, and analytical solutions that support quality and operational decision-making.
- Experience with power generation development and technology.
Leadership & Communication:
- Strong stakeholder management, including influencing without authority.
- Proven experience translating analytics into business strategy and executive narratives.
- Ability to communicate complex analytical findings to both technical and non-technical stakeholders and drive action through data-driven recommendations.
Physical Demands: While performing the duties of this job, the employee is regularly required to talk and hear; and use hands to manipulate objects or controls. The employee is regularly required to stand and walk. On occasion the incumbent may be required to stoop, bend or reach above the shoulders. The employee must occasionally lift up to 25 - 50 pounds. Specific conditions of this job are typical of frequent and continuous computer-based work requiring periods of sitting, close vision and ability to adjust focus.
“We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, disability status, protected veteran status, or any other characteristic protected by law.”
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- Location & working pattern
Waukesha, WI - USA
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